Machine Learning Engineer, AI Safety

NVIDIA Corporation; California; On-site; USD 124,000 - 242,000; Full time

Benefits offered by this job

Equity

Comprehensive benefits package

Job summary

NVIDIA Corporation is seeking a talented Machine Learning Engineer to advance content safety, ML fairness, robustness, and security for LLMs across research and production teams. You will build datasets and models for safety, reliability, and fairness, and apply cutting-edge bias detection techniques in multimodal settings.

You will define metrics, contribute to MLOps tooling, and collaborate with cross-functional teams to deploy safe, scalable AI systems.

Qualifications

• Master’s or PhD in Computer Science, Electrical Engineering, or related field or equivalent experience.
• Minimum of 2+ years of work experience in developing and deploying ML models in production.
• Strong understanding of machine learning principles and algorithms.
• Hands-on programming experience in Python and knowledge of ML frameworks like Keras or PyTorch.
• Experience in Content Safety, ML Fairness, Robustness, AI Model Security, or related areas.
• Experience with large multimodal datasets and multimodal models.
• Excellent problem solving and analytical abilities.
• Excellent collaboration and communication skills.

Responsibilities

• Develop datasets and models for training and evaluating models for Content Safety, ProdSec, Robustness and ML Fairness.
• Research and implement techniques for bias detection and mitigation in LLMs and systems using LLMs like RAGs.
• Define and track metrics for responsible LLM behavior and usage.
• Follow best MLOps practices for automation, monitoring, scale, and safety.
• Contribute to the MLOps platform and develop safety tools for ML teams.
• Collaborate with engineers, data scientists, and researchers to address content safety and ML fairness challenges.

Skills

Python

PyTorch

Keras

ML fundamentals

Education

Master’s or PhD in CS/EE or related field

Tools

PyTorch

Keras

Job description

NVIDIA is in a unique position: we are developing AI-based products across multiple domains, and we collaborate with many interesting AI companies as partners and customers. Ensuring the highest Content Safety possible reduces exposure to inappropriate material. Preventing Bias and Discrimination is essential to both protect individual rights and achieve the best quality of results, including accuracy and completeness of information. By prioritizing safety and fairness, we can ensure that LLMs benefit everyone and contribute to a better future for all.

Our team also works in the area of safety for generative models for language, robustness, and explainability. Our LLMs are a growing area of AI products, including models and services, and we are committed to ensuring that they are used safely and responsibly. We are looking for a talented Machine Learning Engineer to work on Product Security, Content Safety, ML Fairness and Robustness efforts for LLMs across all of our research and production engineering teams. In this role, you’ll have the opportunity to take on innovative problems in machine learning, particularly focused on safety for multi-modal LLMs. This role is directed at assessing, quantifying, and improving the safety and inclusivity of our LLM models in a scalable fashion.

What You’ll Be Doing

• Develop the datasets and models for training and evaluating models and end-to-end systems for Content Safety, ProdSec, Robustness and ML Fairness.
• Research and implement cutting‑edge techniques for bias detection and mitigation in LLMs and systems using LLMs like RAGs.
• Define and track key metrics for responsible LLM behavior and usage.
• Follow the best MLOps practices of automation, monitoring, scale and safety.
• Contribute to the MLOps platform and develop safety tools to help ML teams be more effective.
• Collaborate with other engineers, data scientists, and researchers to develop and implement solutions to content safety and ML fairness challenges.

What We Need To See

• Master’s or PhD in Computer Science, Electrical Engineering or related field - or equivalent experience.
• Minimum of 2+ years of work experience in developing and deploying machine learning models in production.
• Strong understanding of machine learning principles and algorithms.
• Hands‑on programming experience in python and in‑depth knowledge of machine learning frameworks, like Keras or PyTorch.
• Background in one or more of the following broader areas for 1+ years: Content Safety, ML Fairness, Robustness, AI Model Security, or related areas.
• Experience working in a range of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.
• Practice working with large multi-modal datasets and multi-modal models.
• Good at problem‑solving and analytical ability.
• Excellent collaboration and communication skills.
• Demonstrates behaviors that build trust: humility, transparency, respect, and intellectual honesty.

Ways To Stand Out From The Crowd

• Skilled with alignment/fine‑tuning of LLMs - including regular LLMs as well as VLMs (vision‑language models) or any‑to‑text
• Proven experience with multimodal and/or multilingual content safety, legal, and regulatory compliance.
• Knowledge of robustness, including hallucinations, digressions, and generative misinformation.
• Experience with GenAI security, including prompt stability, model extraction, confidentiality/data extraction, integrity, availability, and adversarial robustness.
• Passion for AI and a demonstrated commitment to advancing the field through innovative research, prior scientific research, and publication experience.

With highly competitive salaries and a comprehensive benefits package, Nvidia is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward‑thinking and hardworking people in the world working with us and our engineering teams are growing fast in some of the hottest state of the art fields: Deep Learning, Artificial Intelligence, and Large Language Models. If you're a creative engineer with a real passion for robust and enjoyable user experiences, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 10, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer.

As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.